CN112185148A - 用于评估可能轨迹的方法 - Google Patents
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- CN112185148A CN112185148A CN202010625817.3A CN202010625817A CN112185148A CN 112185148 A CN112185148 A CN 112185148A CN 202010625817 A CN202010625817 A CN 202010625817A CN 112185148 A CN112185148 A CN 112185148A
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DE102019209736.7 | 2019-07-03 | ||
DE102019209736.7A DE102019209736A1 (de) | 2019-07-03 | 2019-07-03 | Verfahren zur Bewertung möglicher Trajektorien |
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DE (1) | DE102019209736A1 (de) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113619603A (zh) * | 2021-08-25 | 2021-11-09 | 华中科技大学 | 一种双阶段自动驾驶车辆调头轨迹规划方法 |
Families Citing this family (9)
Publication number | Priority date | Publication date | Assignee | Title |
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US11900224B2 (en) * | 2019-12-26 | 2024-02-13 | Waymo Llc | Generating trajectory labels from short-term intention and long-term result |
DE102021203440A1 (de) | 2021-04-07 | 2022-10-13 | Zf Friedrichshafen Ag | Computerimplementiertes Verfahren, Computerprogramm und Anordnung zum Vorhersagen und Planen von Trajektorien |
GB2606752A (en) * | 2021-05-20 | 2022-11-23 | Continental Automotive Gmbh | Robot fleet management method and system using a graph neural network |
CN113291320A (zh) * | 2021-06-15 | 2021-08-24 | 苏州智加科技有限公司 | 一种车辆轨迹预测方法、装置、设备及存储介质 |
DE102021208472B3 (de) | 2021-08-04 | 2022-12-01 | Continental Autonomous Mobility Germany GmbH | Computerimplementiertes Verfahren zum Trainieren eines Machine-Learning-Modells für ein Fahrzeug oder einen Roboter |
CN115099009B (zh) * | 2022-05-31 | 2023-08-29 | 同济大学 | 一种基于推理图的混合交通流运动行为建模方法 |
DE102022002457A1 (de) * | 2022-07-05 | 2024-01-11 | Mercedes-Benz Group AG | Verfahren zur Prädiktion eines Einflusses eines Verkehrsteilnehmers auf zumindest einen anderen Verkehrsteilnehmer und Verfahren zum Betrieb eines Fahrzeugs |
CN115687764B (zh) * | 2022-11-01 | 2023-12-01 | 北京百度网讯科技有限公司 | 车辆轨迹评估模型的训练方法、车辆轨迹评估方法和装置 |
DE102023200197A1 (de) | 2023-01-12 | 2024-07-18 | Zf Friedrichshafen Ag | Fahrzeugsystem und Verfahren zur Erhöhung der Verlässlichkeit einer Vorhersage von Zukunftstrajektorien |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9098753B1 (en) * | 2014-04-25 | 2015-08-04 | Google Inc. | Methods and systems for object detection using multiple sensors |
CN107010053A (zh) * | 2015-10-20 | 2017-08-04 | 罗伯特·博世有限公司 | 用于选择优化轨迹的方法 |
DE102017212629A1 (de) * | 2017-07-24 | 2019-01-24 | Bayerische Motoren Werke Aktiengesellschaft | Prädiktion des Verhaltens eines Verkehrsteilnehmers |
US20190164422A1 (en) * | 2017-11-28 | 2019-05-30 | Honda Motor Co., Ltd. | System and method for providing an infrastructure based safety alert associated with at least one roadway |
CN109937343A (zh) * | 2017-06-22 | 2019-06-25 | 百度时代网络技术(北京)有限公司 | 用于自动驾驶车辆交通预测中的预测轨迹的评估框架 |
Family Cites Families (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10108863B2 (en) * | 2015-09-03 | 2018-10-23 | Miovision Technologies Incorporated | System and method for detecting and tracking objects |
CN106114507B (zh) * | 2016-06-21 | 2018-04-03 | 百度在线网络技术(北京)有限公司 | 用于智能车辆的局部轨迹规划方法和装置 |
DE102016215314A1 (de) * | 2016-08-17 | 2018-02-22 | Bayerische Motoren Werke Aktiengesellschaft | Fahrerassistenzsystem, Fortbewegungsmittel und Verfahren zur Prädiktion einer Verkehrssituation |
DE102017216202A1 (de) * | 2017-09-13 | 2019-03-14 | Bayerische Motoren Werke Aktiengesellschaft | Verfahren zur Prädiktion einer optimalen Fahrspur auf einer mehrspurigen Straße |
WO2020027864A1 (en) * | 2018-07-31 | 2020-02-06 | Didi Research America, Llc | System and method for point-to-point traffic prediction |
WO2021003379A1 (en) * | 2019-07-03 | 2021-01-07 | Waymo Llc | Agent trajectory prediction using anchor trajectories |
US11403853B2 (en) * | 2019-08-30 | 2022-08-02 | Waymo Llc | Occupancy prediction neural networks |
US11127142B2 (en) * | 2019-12-31 | 2021-09-21 | Baidu Usa Llc | Vehicle trajectory prediction model with semantic map and LSTM |
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2019
- 2019-07-03 DE DE102019209736.7A patent/DE102019209736A1/de active Pending
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2020
- 2020-07-02 CN CN202010625817.3A patent/CN112185148A/zh active Pending
- 2020-07-02 US US16/920,045 patent/US11501449B2/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9098753B1 (en) * | 2014-04-25 | 2015-08-04 | Google Inc. | Methods and systems for object detection using multiple sensors |
CN107010053A (zh) * | 2015-10-20 | 2017-08-04 | 罗伯特·博世有限公司 | 用于选择优化轨迹的方法 |
CN109937343A (zh) * | 2017-06-22 | 2019-06-25 | 百度时代网络技术(北京)有限公司 | 用于自动驾驶车辆交通预测中的预测轨迹的评估框架 |
DE102017212629A1 (de) * | 2017-07-24 | 2019-01-24 | Bayerische Motoren Werke Aktiengesellschaft | Prädiktion des Verhaltens eines Verkehrsteilnehmers |
US20190164422A1 (en) * | 2017-11-28 | 2019-05-30 | Honda Motor Co., Ltd. | System and method for providing an infrastructure based safety alert associated with at least one roadway |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113619603A (zh) * | 2021-08-25 | 2021-11-09 | 华中科技大学 | 一种双阶段自动驾驶车辆调头轨迹规划方法 |
CN113619603B (zh) * | 2021-08-25 | 2023-02-07 | 华中科技大学 | 一种双阶段自动驾驶车辆调头轨迹规划方法 |
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US11501449B2 (en) | 2022-11-15 |
US20210004966A1 (en) | 2021-01-07 |
DE102019209736A1 (de) | 2021-01-07 |
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